ResNetABI

class mmocr.models.textrecog.ResNetABI(in_channels=3, stem_channels=32, base_channels=32, arch_settings=[3, 4, 6, 6, 3], strides=[2, 1, 2, 1, 1], out_indices=None, last_stage_pool=False, init_cfg=[{'type': 'Xavier', 'layer': 'Conv2d'}, {'type': 'Constant', 'val': 1, 'layer': 'BatchNorm2d'}])

Implement ResNet backbone for text recognition, modified from `ResNet.

<https://arxiv.org/pdf/1512.03385.pdf>`_ and https://github.com/FangShancheng/ABINet

参数

• in_channels (int) – Number of channels of input image tensor.

• stem_channels (int) – Number of stem channels.

• base_channels (int) – Number of base channels.

• arch_settings (list[int]) – List of BasicBlock number for each stage.

• strides (Sequence[int]) – Strides of the first block of each stage.

• out_indices (None | Sequence[int]) – Indices of output stages. If not specified, only the last stage will be returned.

• last_stage_pool (bool) – If True, add MaxPool2d layer to last stage.

forward(x)

参数

x (Tensor) – Image tensor of shape \((N, 3, H, W)\).

返回

Feature tensor. Its shape depends on ResNetABI’s config. It can be a list of feature outputs at specific layers if out_indices is specified.

返回类型

Tensor or list[Tensor]